[1] Sang, D., Fu, R., & Li, Y. (2016). The hot deformation activation energy of 7050 aluminum alloy under three different deformation modes. Metals, 6(3), 49. https://doi.org/10.3390/met6030049
[2] Schindler, I., Kawulok, P., Očenášek, V., Opěla, P., Kawulok, R., & Rusz, S. (2019). Flow stress and hot deformation activation energy of 6082 aluminium alloy influenced by initial structural state. Metals, 9(12), 1248. https://doi.org/10.3390/met9121248
[3] Momeni, A. (2016). The physical interpretation of the activation energy for hot deformation of Ni and Ni–30Cu alloys. Journal of Materials Research, 31(8), 1077-1084. https://doi.org/10.1557/jmr.2016.81
[5] Shi, C., Mao, W., & Chen, X.-G. (2013). Evolution of activation energy during hot deformation of AA7150 aluminum alloy. Materials Science and Engineering: A, 571, 83-91. https://doi.org/10.1016/j.msea.2013.01.080
[6] Shi, C., & Chen, X.-G. (2016). Evolution of activation energies for hot deformation of 7150 aluminum alloys with various Zr and V additions. Materials Science and Engineering: A, 650, 197-209. https://doi.org/10.1016/j.msea.2015.09.105
[7] Son, K. T., Kim, M. H., Kim, S. W., Lee, J. W., & Hyun, S. K. (2018). Evaluation of hot deformation characteristics in modified AA5052 using processing map and activation energy map under deformation heating. Journal of Alloys and Compounds, 740, 96-108. https://doi.org/10.1016/j.jallcom.2017.12.357
[8] Sun, Y., Wan, Z., Hu, L., & Ren, J. (2015). Characterization of hot processing parameters of powder metallurgy TiAl-based alloy based on the activation energy map and processing map. Materials & Design, 86, 922-932. https://doi.org/10.1016/j.matdes.2015.07.140
[9] Zhao, Q., Yang, F., Torrens, R., & Bolzoni, L. (2019). Comparison of hot deformation behaviour and microstructural evolution for Ti-5Al-5V-5Mo-3Cr alloys prepared by powder metallurgy and ingot metallurgy approaches. Materials & Design, 169, 107682. https://doi.org/10.1016/j.matdes.2019.107682
[10] Zhang, J., Di, H., Wang, H., Mao, K., Ma, T., & Cao, Y. (2012). Hot deformation behavior of Ti-15-3 titanium alloy: a study using processing maps, activation energy map, and Zener–Hollomon parameter map. Journal of Materials Science, 47(9), 4000-4011. https://doi.org/10.1007/s10853-012-6253-1
[11] Babu, K. A., Mozumder, Y. H., Saha, R., Sarma, V. S., & Mandal, S. (2018). Hot-workability of super-304H exhibiting continuous to discontinuous dynamic recrystallization transition. Materials Science and Engineering: A, 734, 269-280. https://doi.org/10.1016/j.msea.2018.07.104
[12] Wang, M., Wang, W., Liu, Z., Sun, C., & Qian, L. (2018). Hot workability integrating processing and activation energy maps of Inconel 740 superalloy. Materials Today Communications, 14, 188-198. https://doi.org/10.1016/j.mtcomm.2018.01.009
[13] Yang, P., Liu, C., Guo, Q., & Liu, Y. (2021). Variation of activation energy determined by a modified Arrhenius approach: Roles of dynamic recrystallization on the hot deformation of Ni-based superalloy. Journal of Materials Science & Technology, 72, 162-171. https://doi.org/10.1016/j.jmst.2020.09.024
[14] Fangpo, L., Ning, L., Xiaojian, R., Song, Q., Caihong, L., Jianjun, W., Yang, X., & Bin, W. (2023). Arrhenius constitutive equation and artificial neural network model of flow stress in hot deformation of offshore steel with high strength and toughness. Materials Technology, 38(1), 2264670. https://doi.org/10.1080/10667857.2023.2264670
[15] Abarghooei, H., Arabi, H., Seyedein, S. H., & Mirzakhani, B. (2017). Modeling of steady state hot flow behavior of API-X70 microalloyed steel using genetic algorithm and design of experiments. Applied Soft Computing, 52, 471-477. https://doi.org/10.1016/j.asoc.2016.10.021
[16] Ahmadi, H., Ashtiani, H. R., & Heidari, M. (2020). A comparative study of phenomenological, physically-based and artificial neural network models to predict the Hot flow behavior of API 5CT-L80 steel. Materials Today Communications, 25, 101528. https://doi.org/10.1016/j.mtcomm.2020.101528
[17] Qiao, G. Y., Xiao, F. R., Zhang, X. B., Cao, Y. B., & Liao, B. (2009). Effects of contents of Nb and C on hot deformation behaviors of high Nb X80 pipeline steels. Transactions of Nonferrous Metals Society of China, 19(6), 1395-1399. https://doi.org/10.1016/S1003-6326(09)60039-X
[18] Gomez, M., Valles, P., & Medina, S. F. (2011). Evolution of microstructure and precipitation state during thermomechanical processing of a X80 microalloyed steel. Materials Science and Engineering: A, 528(13-14), 4761-4773. https://doi.org/10.1016/j.msea.2011.02.087
[19] Shen, W., Zhang, C., Zhang, L., Xu, Q., & Cui, Y. (2018). Experimental study on the hot deformation characterization of low-carbon Nb-V-Ti microalloyed steel. Journal of Materials Engineering and Performance, 27, 4616-4624. https://doi.org/10.1007/s11665-018-3594-1
[20] Mendes‐Fonseca, N., Rodrigues, S. F., Guo, B., & Jonas, J. J. (2019). Dynamic transformation during the simulated hot rolling of an API‐X80 steel. Steel Research International, 90(8), 1900091. https://doi.org/10.1002/srin.201900091
[21] Eskandari, H., Reihanian, M., & Zaree, S. A. (2024). Constitutive modeling, processing map optimization, and recrystallization kinetics of high-grade X80 pipeline steel. Journal of Materials Research and Technology, 33, 2315-2330. https://doi.org/10.1016/j.jmrt.2024.09.217
[22] Eskandari, H., Reihanian, M., & Alavi Zaree, S. (2023). An analysis of efficiency parameter and its modifications utilized for development of processing maps. Iranian Journal of Materials Forming, 10(4), 45-51. https://doi.org/10.22099/ijmf.2024.49537.1283
[23] Niu, T., Kang, Y. l., Gu, H. W., Yin, Y. Q., Qiao, M. L., & Jiang, J. X. (2010). Effect of Nb on the dynamic recrystallization behavior of high-grade pipeline steels. International Journal of Minerals, Metallurgy, and Materials, 17(6), 742-747. https://doi.org/10.1007/s12613-010-0383-8
[25] Wang, L., Ji, L., Yang, K., Gao, X., Chen, H., & Chi, Q. (2022). The flow stress–strain and dynamic recrystallization kinetics behavior of high-grade pipeline steels. Materials, 15(20), 7356. https://doi.org/10.3390/ma15207356
[26] Zhao, J., Hu, W., Wang, X., Kang, J., Cao, Y., Yuan, G., Di, H., & Misra, R. (2016). A Novel thermo-mechanical controlled processing for large-thickness microalloyed 560 MPa (X80) pipeline strip under ultra-fast cooling. Materials Science and Engineering: A, 673, 373-377. https://doi.org/10.1016/j.msea.2016.07.089
[27] Machado, F. R. d. S., Ferreira, J. C., Rodrigues, M. V. G., Lima, M. N. d. S., Loureiro, R. d. C. P., Siciliano, F., Silva, E. S., Reis, G. S., Sousa, R. C. d., & Aranas Jr, C. (2022). Dynamic ferrite formation and evolution above the Ae3 temperature during plate rolling simulation of an API X80 steel. Metals, 12(8), 1239. https://doi.org/10.3390/met12081239
[28] Ma, G., Chen, Y., Wu, G., Wang, S., Li, T., Liu, W., Wu, H., Gao, J., Zhao, H., & Zhang, C. (2023). The effects of microalloying on the precipitation behavior and strength mechanisms of X80 high-strength pipeline steel under different processes. Crystals, 13(5), 714. https://doi.org/10.3390/cryst13050714
[29] Silva, R. A., Pinto, A. L., Kuznetsov, A., & Bott, I. S. (2018). Precipitation and grain size effects on the tensile strain-hardening exponents of an API X80 steel pipe after high-frequency hot-induction bending. Metals, 8(3), 168. https://doi.org/10.3390/met8030168
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